DNA Sequence Data Research Articles

Scuphr: A probabilistic framework for cell lineage tree reconstruction

Cell lineage tree reconstruction methods are developed for various tasks, such as investigating the development, differentiation, and cancer progression. Single-cell sequencing technologies enable more thorough analysis with higher resolution. We present Scuphr, a distance-based cell lineage tree reconstruction method using bulk and single-cell DNA sequencing data from healthy tissues. Common challenges of single-cell DNA sequencing, such as allelic dropouts and amplification errors, are included in Scuphr. Scuphr computes the distance between cell pairs and reconstructs the lineage tree using the neighbor-joining algorithm. With its embarrassingly parallel design, Scuphr can do faster analysis than the state-of-the-art methods while obtaining better accuracy. The method’s robustness is investigated using various synthetic datasets and a biological dataset of 18 cells.

Taxonomy and phylogeny of the family Suberitidae (Porifera: Demospongiae) in California

This study presents a comprehensive taxonomic revision of the family Suberitidae (Porifera: Demospongiae) for California, USA. We include the three species previously known from the region, document two additional species previously known from other regions, and formally describe four new species as Pseudosuberites latke sp. nov., Suberites californiana sp. nov., Suberites kumeyaay sp. nov., and Suberites agaricus sp. nov. Multi-locus DNA sequence data is presented for seven of the nine species, and was combined with all publicly available data to produce the most comprehensive global phylogeny for the family to date. By integrating morphological and genetic data, we show that morphological characters may be sufficient for regional species identification but are likely inadequate for global classification into genera that reflect the evolutionary history of the family. We therefore propose that DNA sequencing is a critical component to support future taxonomic revisions.

Interaction of sound-audition traits between eared insects and arthropodophagous bats: using a DNA approach to assess diet

Abstract Arthropod–bat interactions are often considered as a base model for studying factors underlying predator–prey coevolutionary processes. Bats developed ultrasonic echolocation to hunt, and in response some arthropods developed defense mechanisms such as ultrasonic hearing, allowing them to elude bat predators. The present study analyzes the feeding patterns of bats, focusing on sonic-auditory sensory mechanisms in predator–prey interactions. Next-generation DNA sequence data from fecal samples were used to analyze the diet of 17 bat species from Mexico. Arthropod prey taxa were classified according to their auditory traits, and echolocation data were recompiled from literature review. We: (i) classified arthropod families according to their hearing ability; (ii) estimated arthropod taxon richness and proportion in the diet of each bat species; and (iii) used multidimensional scaling, principal component analysis, and regression to analyze prey consumption patterns in relation to their auditory traits and in relation to echolocation characteristics of bats. Finally, we analyzed the relationship between foraging time and auditory characteristics of prey. Families with hearing organs correspond to the orders Lepidoptera and Orthoptera. We registered 20 families of Lepidoptera and 5 of Orthoptera—7 and 3 with hearing organs, respectively. Of these orders, families lacking ears were recorded in the diet of a few bat species. Our results support the allotonic frequency hypothesis predicting a difference in emission frequency intervals between predator and prey. However, we found that the consumption of earless moths is less frequent and is related to diurnal and twilight activity—hence, their consumption is limited to bat species foraging early. Results indicate bats feed on arthropod prey successfully despite the ultrasonic hearing ability of the prey. These results may be due to counteradaptations that allow maintenance of an asymmetric “arms race” between bats and eared insects that favors the predator.

Abstract PO3-23-09: ESR1 mutations drive resistance to CDK4/6 inhibitors in ER+ Breast Cancer

Abstract Mutations in ESR1 (the gene encoding the estrogen receptor, ERα) are major drivers of resistance to antiestrogen therapy in ER+ breast cancer. However, it remains unclear whether ESR1 mutations also drive resistance to CDK4/6 inhibitors (CDK4/6i). We analyzed de-identified next generation sequencing (NGS) data of tumor tissue DNA (n=1,820) and circulating tumor (ct) DNA (n=2,138) from patients with ER+/HER2- metastatic breast cancer. NGS of tumor tissue DNA and ctDNA previously had been performed using the Tempus xT tumor assay (595-648 genes) and Tempus xF liquid biopsy (105-523 genes), respectively. Patients were stratified into treated (xT:1,070; xF:1,885) or untreated (xT:750; xF:253) with CDK4/6i prior to biopsy, and untreated patients were restricted to those biopsied within 30 days of metastatic diagnosis. ESR1 was the only gene for which mutations were significantly enriched in patients who received CDK4/6i vs. those who did not in both xT (32% vs. 4.8%, q< 0.001) and xF (29% vs. 9.5%, q< 0.001) cohorts. To determine whether ESR1 mutations drive resistance to CDK4/6i, we used MCF-7 cells carrying ESR1 wild-type (WT), Y537S, or D538G ‘hotspot’ knock-in mutations to assess cell proliferation upon treatment with the CDK4/6i palbociclib. Cells harboring the Y537S and D538G mutations displayed a 3-fold increase in the IC50 of palbociclib single agent compared to ESR1WT cells. When treated with palbociclib + fulvestrant or palbociclib + estrogen-free medium (mimicking estrogen suppression in patients treated with aromatase inhibitors), cells harboring the Y537S and D538G mutations displayed an 11.2 to 46.9-fold increase in the IC50 of palbociclib. Treatment with palbociclib arrested growth of MCF-7 ESR1WT xenografts established in ovariectomized nude mice whereas MCF-7 ESR1Y537S and MCF-7 ESR1D538G tumors continued to grow. These results suggest that ESR1 mutations enable cell proliferation and tumor growth in the presence of CDK4/6i and the combination of CDK4/6i + antiestrogens. Next, we performed RNA-seq to investigate the mechanisms underlying ESR1 mutation-mediated resistance to CDK4/6i. Gene set enrichment analysis (GSEA) of the RNA-seq data showed significant upregulation of cell cycle-related Hallmark gene signatures such as E2F targets, G2/M checkpoints, and mitotic spindle in ESR1Y537S vs. ESR1WT and ESR1D538G vs. ESR1WT MCF-7 cells upon treatment with palbociclib. Upregulation of these gene signatures in ESR1-mutant vs. WT cells was also observed upon treatment with palbociclib + fulvestrant and palbociclib in estrogen-free media, suggesting that ESR1 mutations hamper the inhibitory effects of CDK4/6i alone or in combination with antiestrogens on cell cycle progression. Additionally, RNA-seq analysis showed that cells expressing either the Y537S or D538G mutation had elevated basal gene signatures (METABRIC_basal, TCGA_basal, and Huper_basal) compared to ESR1WT cells, consistent with previous studies suggesting that ESR1 mutations promote a luminal-to-basal subtype switch in ER+ breast cancers. We are currently investigating whether this lineage reprogramming underlies resistance to CDK4/6i in ESR1-mutant cells. In addition, we will validate our findings by analyzing the tumor tissue transcriptome from the patients included in this study. Conclusions: ESR1 mutations are enriched following treatment with CDK4/6i in a cohort of 3,958 patients with ER+/HER2- metastatic breast cancer. Mutations in ESR1 in ER+ breast cancer cells directly promote resistance to CDK4/6i alone or CDK4/6i + antiestrogens in vitro and in vivo. Citation Format: M Rosario Chica-Parrado, Chang-Ching Lin, Ellen Jaeger, Michelle Harris, Lei Guo, Emmanuel Bikorimana, Fabiana Napolitano, Calvin Chao, Ariella Hanker, Carlos Arteaga. ESR1 mutations drive resistance to CDK4/6 inhibitors in ER+ Breast Cancer [abstract]. In: Proceedings of the 2023 San Antonio Breast Cancer Symposium; 2023 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2024;84(9 Suppl):Abstract nr PO3-23-09.

Abstract PL-01: Breast Cancer Evolution, Immune Evasion and Metastasis Driven by Chromosomal Instability

Abstract Chromosomal instability (CIN) is a poor prognostic feature with high prevalence in breast cancer and is responsible for driving Somatic Copy Number Aberrations and Intratumour Heterogeneity (ITH) within subclones during breast cancer evolution. We have observed that SCNAs are enriched in metastatic samples, including gains in chromosome 11q13.3 (encompassing CCND1) in HER2+ breast cancer. However, there have thus far been no prospective, comprehensive studies of intratumor heterogeneity in breast cancer. We will present data from TRACERx Breast/SCANDARE a prospective, multicentre study of triple-negative breast cancer (TNBC) in which multi-region biopsies have been collected from primary TNBC prior to neoadjuvant treatment, and at longitudinal time points including surgery and relapse. We find prevalent intratumor heterogeneity in somatic mutations and SCNAs in the primary tumor prior to treatment. We have leveraged the rich clinical annotation in this cohort to correlate intratumor heterogeneity scores with key clinical outcomes, including treatment response (pathological complete response to neoadjuvant chemotherapy) and survival. We find that CIN manifests as oncogenic amplification on extrachromosomal DNA (ecDNA), which plays a pivotal role in driving drug resistance and tumor evolution. Through analysis of Whole Genome Sequencing data from 2936 breast tumors from the Genomics England breast cancer cohort, we have identified focal amplifications driven by ecDNA in 46.4% of HER2+ breast cancers. EcDNA were enriched in metastatic tumors and was associated with poor clinical outcomes. In addition to oncogenic amplifications such as HER2 derived from ecDNA during cancer evolution, ecDNAs contained immunomodulatory genes associated with reduced T cell infiltration. Further Immune-modulation by CIN results from loss of heterozygosity of the HLA locus (HLA LOH) and is a prevalent subclonal event in breast cancer. CIN is further drives haploid LOH, resulting in the high prevalence of whole genome doubling and further CIN in TNBC. Tumors are heterogeneous compositions of distinct clones with different compliments of SCNAs and varying levels of fitness, hence measuring the proliferation of individual clones to predict future evolutionary outcomes is likely to be critical. We have developed SPRINTER (Single-cell Proliferation Rate Inference in Non-homogeneous Tumours through Evolutionary Routes), a novel computational method to measure proliferation rates in individual tumour clones using single-cell whole-genome DNA sequencing data. We applied SPRINTER to 42,009 triple negative breast cancer cells, demonstrating significant proliferative heterogeneity between distinct tumor clones. Importantly, we show a correlation between higher proliferation rates and increased rates of somatic variants, suggesting proliferation links to clone evolvability. Taken together, these complimentary analyses provide evidence for the importance of CIN in driving ITH, selection, metastasis and immune evasion and provide a framework to determine recurrent evolutionary patterns in breast cancer evolution. Citation Format: C. Swanton. Breast Cancer Evolution, Immune Evasion and Metastasis Driven by Chromosomal Instability [abstract]. In: Proceedings of the 2023 San Antonio Breast Cancer Symposium; 2023 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2024;84(9 Suppl):Abstract nr PL-01.

Genomic Profiling of Rare Undifferentiated Sarcomatoid Subtypes of Pancreatic Carcinomas: In Search of Therapeutic Targets

PURPOSE The highly aggressive undifferentiated sarcomatoid carcinoma (USC) subtype of pancreatic ductal adenocarcinoma (PDAC) remains poorly characterized because of its rarity. Previous case reports suggest that immune checkpoint inhibitors could be a promising treatment strategy, but the prevalence of established predictive biomarkers of response is largely unknown. The objective of this study was to leverage comprehensive genomic profiling of USC PDAC tumors to determine the prevalence of biomarkers associated with potential response to targeted therapies. METHODS USC tumors (n = 20) underwent central pathology review by a board-certified gastrointestinal pathologist to confirm the diagnosis. These samples were compared with non-USC PDAC tumors (N = 5,562). Retrospective analysis of DNA and RNA next-generation sequencing data was performed. RESULTS USC PDACs were more frequently PD-L1+ by immunohistochemistry than non-USC PDAC (63% v 16%, respectively, P < .001). Furthermore, USC PDAC had an increase in neutrophils (8.99% v 5.55%, P = .005) and dendritic cells (1.08% v 0.00%, q = 0.022) and an increased expression of PDCD1LG2 (4.6% v 1.3%, q = 0.001), PDCD1 (2.0% v 0.8%, q = 0.060), and HAVCR2 (45.9% v 21.7%, q = 0.107) than non-USC PDAC. Similar to non-USC PDAC, KRAS was the most commonly mutated gene (86% v 90%, respectively, P = 1). CONCLUSION To our knowledge, this work represents the largest molecular analysis of USC tumors to date and showed an increased expression of immune checkpoint genes in USC tumors. These findings provide evidence for further investigation into immune checkpoint inhibitors in USC tumors.

Morphology, morphogenesis and molecular phylogeny of the new soil ciliate, Lamtostyla paravitiphila nov. spec. (Ciliophora, Hypotrichia)

The morphology and morphogenesis of Lamtostyla paravitiphila nov. spec., a novel soil hypotrichous ciliate collected from eastern China, were investigated based on live observations and protargol-stained specimens. The new species is morphologically characterized as follows: seven to twelve macronuclear nodules, cortical granules absent, 19–26 adoral membranelles, three or four frontoventral cirri, the amphisiellid median cirral row extends to about mid-body and composed of 12–18 cirri, two or three transverse cirri, 27–39 left and 30–41 right marginal cirri, three almost bipolar dorsal kineties. Morphogenetically, it is characterized by the initial formation of six frontal-ventral-transverse cirral anlagen as primary primordia. Notably, the amphisiellid median cirral row and the posterior frontoventral cirrus (or cirri) contribute to the development of the frontal-ventral-transverse cirral anlagen, while the buccal cirrus may not participate in this process. Phylogenetic analyses based on small subunit ribosomal DNA sequence data indicate that the Lamtostyla species with available molecular data do not form a monophyletic group.

Deep learning model for predicting genetic diseases using DNA sequence data

 The emergence of machine learning in the recent decade has excelled in determining new potential features and nonlinear relationships existing between the data derived from the DNA sequences of genetic diseases. Machine learning also enhances the process of handling data with maximum predicted variables compared to observations during the data mining process of prediction. In this context, our study presents a deep learning model for predicting Transcription Factor Binding Sites (TFBS) in DNA sequences, with a focus on features within genetic data associated with diseases. Transcription Factors (TFs) play a crucial role in modulating gene expression by binding to TFBS. The accurate prediction of TFBS is essential for understanding genome function and evolution. Thus, we develop an efficient deep learning model that considers TFBS prediction as a nucleotide-level binary classification task. In our proposed model, first we create an input matrix using the original DNA sequences. Next, we encode these DNA sequences using one-hot encoding, representing them as a sequence of numerical values. We then employ three convolutional layers, allowing our model to capture intricate patterns and motif features over a larger spatial range. To capture important features within the DNA sequence and to focus on them, we incorporate an attention layer. Finally, a dense layer, consisting of two fully connected layers and a dropout layer, calculates the probability of TF binding site occurrence based on the features learned by the proposed model. Our experimental results, using in-vivo datasets obtained from Chip-seq, demonstrate the superior performance of our proposed deep learning model in TFBS prediction compared to other existing state-of-the-art methods. The improvement in accuracy is due to additional layers of CNN and then an attention layer in the model. Thus, this result in a better performance of our approach in predicting the transcription factor binding sites and enhancing our understanding of gene regulation and genome function.

ScGAL: unmask tumor clonal substructure by jointly analyzing independent single-cell copy number and scRNA-seq data

BackgroundAccurately deciphering clonal copy number substructure can provide insights into the evolutionary mechanism of cancer, and clustering single-cell copy number profiles has become an effective means to unmask intra-tumor heterogeneity (ITH). However, copy numbers inferred from single-cell DNA sequencing (scDNA-seq) data are error-prone due to technically confounding factors such as amplification bias and allele-dropout, and this makes it difficult to precisely identify the ITH.ResultsWe introduce a hybrid model called scGAL to infer clonal copy number substructure. It combines an autoencoder with a generative adversarial network to jointly analyze independent single-cell copy number profiles and gene expression data from same cell line. Under an adversarial learning framework, scGAL exploits complementary information from gene expression data to relieve the effects of noise in copy number data, and learns latent representations of scDNA-seq cells for accurate inference of the ITH. Evaluation results on three real cancer datasets suggest scGAL is able to accurately infer clonal architecture and surpasses other similar methods. In addition, assessment of scGAL on various simulated datasets demonstrates its high robustness against the changes of data size and distribution. scGAL can be accessed at: https://github.com/zhyu-lab/scgal.ConclusionsJoint analysis of independent single-cell copy number and gene expression data from a same cell line can effectively exploit complementary information from individual omics, and thus gives more refined indication of clonal copy number substructure.

First Report of Rust Caused by Phakopsora nishidana on Creeping Fig, Ficus pumila, in South Africa.

Phakopsora nishidana has recently been reported as the causal organism of rust on edible fig, Ficus carica in South Africa (SA) (Boshoff et al. 2022). This contradicted reports by Doidge (1927, 1950) and Verwoerd (1929) who listed Cerotelium fici as the causal organism of the disease in SA. Similarities in urediniospore morphology and differing taxonomic interpretations most likely contributed to the use of both pathogen names as the causal agents for fig rust (Boshoff et al. 2022; Padamsee and McKenzie 2024). In January 2023 rust was commonly observed on nursery specimens of creeping fig, Ficus pumila, a popular evergreen and fast-growing garden plant in SA. Ficus pumila is native to southern China, Indochina, and eastern Asia but has been introduced to many countries worldwide (https://powo.science.kew.org/ accessed 20 March 2024). The F. pumila rust isolate collected in Somerset West (34°07'00.70"S, 18°52'41.75"E; Western Cape (WC) province) was identified using the sequenced 5.8S rRNA-ITS2-28S rRNA locus. When used in a BLAST analysis, this F. pumila isolate (GenBank accession number OR835538) shared the best homology with the Vermont P. nishidana isolate (34°24'33.37"S, 19°08'59.24"E) (MZ047090; e-value 0.0, 99.7% identity, 1400/1404 bp) reported on edible fig by Boshoff et al. (2022). Other P. nishidana isolates with excellent homology were KY764080 (e-value 0.0, 99.8% identity, 1012/1014 bp), KY764081 (e-value 0.0, 99% identity, 882/885 bp) and MF580676 (e-value 0.0, 99.3% identity, 981/988 bp). Accessions were used in a phylogenetic study that included four other rust samples collected from F. carica trees in Somerset West, WC (OR835534; 34°03'37.26"S, 18°51'02.18"E), Onrus River, WC (OR835535; 34°24'43.10"S, 19°09'57.99"E), Elgin, WC (OR835536; 34°14'31.37"S, 19°03'05.38"E), and Bloemfontein, Free State province (OR835537; 29°05'05.1"S 26°09'09.5"E). Reference sequences were as described in Boshoff et al. (2022). Despite limited variation, all six South African isolates, including the F. pumila isolate, grouped with the three P. nishidana reference isolates, but separate from the three P. myrtacearum isolates collected from eucalyptus trees (Maier et al. 2016). Uredinia on F. pumila leaves were mostly hypophyllous and surrounded by a halo of brown, necrotic tissue. On the upper leaf surface, the lesions appeared as small, dark leaf spots with infrequent sporulation. Urediniospores were echinulate, mostly obovoid or elliptical and their cell walls pale-yellow to yellowish-brown. The mean width and length of urediniospores were 16.7 x 21.3 µm. No telia were observed. Applying standard rust inoculation and incubation procedures (Boshoff et al. 2022), F. pumila plants inoculated with P. nishidana isolate PREM63073 produced sporulating uredinia on the abaxial surface of leaves. Likewise, inoculation of F. carica cv. Kadota leaves with the F. pumila isolate OR835538 yielded sporulating lesions containing urediniospores typical of P. nishidana, on the lower surface. Based on both the DNA sequence data and controlled infection studies, our study confirmed the host status of F. pumila for P. nishidana. The occurrence of rust on creeping fig plants in nurseries, the evergreen status of the creeper, and thus the potential to harbor the pathogen during winter, are likely to contribute to the spread of fig rust in SA.

Development and utilization of genome-wide InDel markers in Sorghum [Sorghum bicolor (L.) Moench]

Sorghum (Sorghum bicolor L. Moench) has become an increasingly valuable crop for food, feed, and especially bioenergy feedstock production, which makes the crop extremely attractive for studying genomics and genetic diversity. Molecular markers and genomics play essential roles in sorghum breeding. The rapid development of next-generation sequencing technology has facilitated the identification of genome-wide insertion-deletion (InDel) polymorphisms, enabling the efficient construction of InDel markers that are suitable for user-friendly PCR. This study was conducted with the objective of discovering and developing InDel markers using double digest restriction site-associated DNA sequencing (ddRAD-Seq) data. A total of 19,226 InDels distributed across 10 chromosomes in the sorghum genome was identified. Of those, deletions constituted 65.7% while the remain was insertions. A comprehensive analysis of all the chromosomes revealed a total of 80 InDel sites with a minimum length of 10 bp. For a good conversion of the InDel regions to beneficial molecular markers, specific primers were designed for the amplification of 47 InDel regions that were selected for further investigation. A diverse panel of sorghum consisting of 16 accessions served a source for the developed InDel markers validation. Of the 47 InDel markers, 14 were tested across 16 sorghum accessions and were demonstrated their helpfulness for marker-assisted selection in sorghum. The polymorphic information content (PIC) values of the 16 markers varied between 0.11 and 0.38, with an average of 0.28. The findings of this study indicated that the identification of InDels and the development of molecular markers for sorghum were accomplished using the ddRAD-Seq data.

Systematic revision of species of Atractilina and Spiropes hyperparasitic on Meliolales (Ascomycota) in the tropics.

Atractilina Dearn. & Barthol. and Spiropes Cif. are genera of asexual fungi that comprise species mainly hyperparasitic on black mildews (Meliolales, Ascomycota). Although a common group of anamorphic fungi, they have been described up to now only by morphology and their systematic position is unknown. The present study provides a morphological treatise of all known species of Atractilina and Spiropes hyperparasitic on Meliolales, including insights into their systematic position, based on DNA sequences generated here for the first time. The study was conducted, based on 33 herbarium specimens and 23 specimens recently collected in Benin and Panama. The obtained DNA sequence data (28S rDNA and ITS rDNA) of A.parasitica and of two species of Spiropes show systematic placements in the Dothideomycetes and Leotiomycetes, respectively. The sequence data of the two Spiropes spp. do not group together. Moreover, the anamorph-teleomorph connection between Atractilinaparasitica and Malacariameliolicola, a pseudothecioid fungus, is confirmed. Three species in the genus Spiropes are proposed as new to science, namely S.angylocalycis, S.carpolobiae and S.croissantiformis. Four species are reported for Benin for the first time, three species for Panama and one species for mainland America. Atractilina and Spiropes are currently two genera with highly heterogeneous species and they might have to be split in the future, once the taxonomic concepts are validated by morphology and molecular sequence data.

A process to reanalyze clinical DNA sequencing data for biomarker matching in the Lung-MAP Master Protocol.

For cancer clinical trials that require central confirmation of tumor genomic profiling, exhaustion of tissue from standard-of-care testing may prevent enrollment. For Lung-MAP, a master protocol that requires results from a defined centralized clinical trial assay to assign patients to a therapeutic substudy, we developed a process to repurpose existing commercial vendor raw genomic data for eligibility: genomic data reanalysis (GDR). Molecular results for substudy assignment were successfully generated for 369 of the first 374 patients (98.7%) using GDR for Lung-MAP, with a median time from request to result of 9 days. During the same period, 691 of 791 (87.4%) tissue samples received successfully yielded results, in a median of 14 days beyond sample acquisition. GDR is a scalable bioinformatic pipeline that expedites reanalysis of existing data for clinical trials in which validated integral biomarker testing is required for participation.

Accelerated somatic mutation calling for whole-genome and whole-exome sequencing data from heterogenous tumor samples.

Accurate detection of somatic mutations in DNA sequencing data is a fundamental prerequisite for cancer research. Previous analytical challenge was overcome by consensus mutation calling from four to five popular callers. This, however, increases the already nontrivial computing time from individual callers. Here, we launch MuSE 2, powered by multi-step parallelization and efficient memory allocation, to resolve the computing time bottleneck. MuSE 2 speeds up 50 times than MuSE 1 and 8-80 times than other popular callers. Our benchmark study suggests combining MuSE 2 and the recently accelerated Strelka2 achieves high efficiency and accuracy in analyzing large cancer genomic datasets.

Abstract SY02-03: Stochastic modeling of clonal evolution in carcinogenesis

Abstract In order to develop strategies that can detect cancer earlier, we need to better understand the dynamics of cancer evolution during the human lifetime. Starting from gestation, this includes measuring both the timing of early somatic mutations that lead to clonal mosaicism as well as the growth rates of mutated clones that carry higher potential for malignant transformation. Continuous observation of this evolving clonal composition across a lifetime is not feasible, therefore mathematical models are needed to integrate data from longitudinal and cross-sectional samples and infer these dynamics. Stochastic models of clonal evolution offer such a framework and provide a means for predicting individual clone trajectories into the future. Furthermore, if measurements of evolution are to be utilized clinically for early detection and patient risk stratification, faster methods to apply these models to data are required. To this end, we derived methods using coalescent theory for single-cell DNA sequencing data that enable instantaneous estimation of the growth rate of a clone along with its confidence intervals. Our tool is available in an open source R package, cloneRate, and provides the first method for constructing valid confidence intervals of growth rates analytically without having to rely on Bayesian inference techniques and complex simulations. When applying our methods to recent datasets derived from normal and neoplastic human blood cells, we quantified increased fitness effects of multi-hit driver mutations and found that higher initial clone growth rates led to decreased time to cancer diagnosis in patients. We can also use these models to estimate other important biological parameters that are difficult to measure in vivo such as bounds for total number of hematopoietic stem cells and expansion rates in early development. Ultimately, the ability to easily and quickly parameterize clonal dynamics in individual patients will benefit future early detection efforts and screening strategies for many cancer types. Citation Format: Kit Curtius. Stochastic modeling of clonal evolution in carcinogenesis [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 2 (Late-Breaking, Clinical Trial, and Invited Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(7_Suppl):Abstract nr SY02-03.

A review: Molecular identification of orchid mycorrhiza

Orchids are a diverse and widespread family of flowering plants, with over 25,000 known species and more than 100,000 hybrids and cultivars. Orchids are characterised by their often showy and highly specialised flowers and have unique and intricate floral. Orchids are known to be highly dependent on their mycorrhizal fungi for nutrient uptake, especially during the early stages of their development. Orchid seeds lack the endosperm present in most other seeds, which means they cannot germinate without a source of nutrition. The relationship between orchids and mycorrhiza is known as orchid mycorrhizae or orchid mycorrhiza. In orchid mycorrhiza, the orchid plant forms a mutualistic relationship with certain species of fungi that are able to penetrate the orchid’s roots and colonise its tissues to provides the orchid with essential nutrients. Orchid mycorrhizal fungi are often highly specific, meaning that they can only form partnerships with certain orchid species, and vice versa. The importance of mycorrhizal fungi in the orchid life cycle is crucial from both evolutionary and ecological standpoints. Therefore, it is essential to acquire a thorough comprehension of this relationship and develop methodologies for isolating, identifying, and preserving significant fungal strains that are associated with different orchid species. In recent years, there has been a considerable increase in research concentration on mycorrhizal interactions in orchids. However, certain inquiries remain unresolved pertaining to the fungal communities associated with orchids as well as the divergences notices across different species and geographical locales. The present paper provides a through, and extensive analysis of the fungal life associated with orchids. This article presents a succinct overview of the molecular techniques utilised by researchers globally to isolate and identify peloton-forming fungi in both temperate terrestrial and tropical orchids. The review begins by proving a concise introduction to the background material regarding the wide range of fungal species that are linked with orchids. It then proceeds to explores the topic of orchid mycorrhizal fungi (OMF) and orchid non-mycorrhizal fungi (ONF). The subsequent analysis explores the crucial function that orchid mycorrhizal fungi play in the processes of seed germination and development. Moreover, the study elaborates on the methodologies utilised for isolating fungi, extracting fungal DNA, selecting primers, amplifying DNA and subsequent analysis sequence data. This article considers several molecular identification approaches that are used in studying orchid endophytic mycorrhizal. Using molecular approaches, orchid mycorrhizal can be further explored and identified.  

Ngāokeoke Aotearoa: The Peripatoides Onychophora of New Zealand.

(1) Background: Originally described as a single taxon, Peripatoides novaezealandiae (Hutton, 1876) are distributed across both main islands of New Zealand; the existence of multiple distinct lineages of live-bearing Onychophora across this spatial range has gradually emerged. Morphological conservatism obscured the true endemic diversity, and the inclusion of molecular tools has been instrumental in revealing these cryptic taxa. (2) Methods: Here, we review the diversity of the ovoviviparous Onychophora of New Zealand through a re-analysis of allozyme genotype data, mitochondrial DNA cytochrome oxidase subunit I sequences, geographic information and morphology. (3) Results: New analysis of the multilocus biallelic nuclear data using methods that do not require a priori assumptions of population assignment support at least six lineages of ovoviviparous Peripatoides in northern New Zealand, and mtDNA sequence variation is consistent with these divisions. Expansion of mitochondrial DNA sequence data, including representation of all existing taxa and additional populations extends our knowledge of the scale of sympatry among taxa and shows that three other lineages from southern South Island can be added to the Peripatoides list, and names are proposed here. In total, 10 species of Peripatoides can be recognised with current data.

Phylogeography, systematics, and conservation status of pocket mice (Chaetodipus) of the Sonoran–Sinaloan thorn forest

Abstract Three species of pocket mice (Chaetodipus artus, C. goldmani, and C. pernix) characterize the Sinaloan subregion of the Sonoran regional desert. They occur primarily in Sinaloan thornscrub and monsoon (dry deciduous) forest biotic communities, both of which have suffered from agricultural conversion. Sinaloan thornscrub occurs along the coastal plains of southern Sonora and Sinaloa, México, and grades into monsoon forest in the foothills of the Sierra Madre Occidental. We describe the geographical and ecological distributions of the 3 species of Chaetodipus, evaluate evolutionary relationships within each species based on mitochondrial DNA sequence data, and compare these to previously described phenetic, allozymic, and chromosomal variation. We elevate the subspecies of C. pernix to full species, delineate evolutionary units within C. goldmani and C. artus that we formally recognize as subspecies, and evaluate the conservation status of all 3 species of Chaetodipus.

Technological Development and Advances for Constructing and Analyzing Plant Pangenomes.

A pangenome captures the genomic diversity for a species, derived from a collection of genetic sequences of diverse populations. Advances in sequencing technologies have given rise to three primary methods for pangenome construction and analysis: de novo assembly and comparison, reference genome-based iterative assembly, and graph-based pangenome construction. Each method presents advantages and challenges in processing varying amounts and structures of DNA sequencing data. With the emergence of high-quality genome assemblies and advanced bioinformatic tools, the graph-based pangenome is emerging as an advanced reference for exploring the biological and functional implications of genetic variations.

Technical Note on the quality of DNA sequencing for the molecular characterisation of genetically modified plants.

As part of the risk assessment (RA) requirements for genetically modified (GM) plants, according to Regulation (EU) No 503/2013 and the EFSA guidance on the RA of food and feed from GM plants (EFSA GMO Panel 2011), applicants need to perform a molecular characterisation of the DNA sequences inserted in the GM plant genome. This Technical Note to the applicants puts together requirements and recommendations for the quality assessment of the methodology, analysis and reporting when DNA sequencing is used for the molecular characterisation of GM plants. In particular, it applies to the use of Sanger sequencing and next-generation sequencing for the characterisation of the inserted genetic material and its flanking regions at each insertion site, the determination of the copy number of all detectable inserts and the analysis of the genetic stability of the inserts. This updated document replaces the EFSA 2018 Technical Note and reflects the current knowledge in scientific-technical methods for generating and verifying, in a standardised manner, DNA sequencing data in the context of RA of GM plants. It does not take into consideration the verification and validation of the detection method which remains under the remit of the Joint Research Centre (JRC).